Materialise (MTLS) Research & Development (2013 - 2026)
Materialise's Research & Development came in at -$14.31 million for the quarter ended Jun 30, 2026, compared with -$12.59 million a year earlier.
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Analysis
Materialise (MTLS) Research & Development (2013 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Materialise reported Research & Development of -$55.71 million; for the year ended Dec 31, 2025, it came in at -$52.07 million.
- Going back by year, Research & Development was -$48.06 million in the year ended Dec 31, 2024, -$41.21 million in the year ended Dec 31, 2023, -$12.26 million in the year ended Dec 31, 2022 and -$30.46 million in the year ended Dec 31, 2021.
- The figure for the quarter ended Jun 30, 2026 represents the lowest quarterly Research & Development in data going back to the quarter ended Jun 30, 2013.
- Business Quant data shows MTLS's Research & Development at -$13.92 million (quarter ended Mar 31, 2026), -$14.1 million (quarter ended Dec 31, 2025) and -$13.37 million (quarter ended Sep 30, 2025) in the three quarters before the quarter ended Jun 30, 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | R&D (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 466.13 Bn | 435.08 Bn | 1.64 Bn | 192.51 Mn |
| 2 | Oracle | 383.82 Bn | 255.95 Bn | - | 2.40 Bn |
| 3 | Sap Se | 263.61 Bn | 191.39 Bn | 8.40 Bn | -2.14 Bn |
| 4 | Salesforce | 198.89 Bn | 154.76 Bn | 8.70 Bn | 1.69 Bn |
| 5 | ServiceNow | 149.64 Bn | 128.10 Bn | 2.82 Bn | 915.00 Mn |
| 6 | Automatic Data Processing | 115.45 Bn | 97.58 Bn | 2.51 Bn | 265.90 Mn |
| 7 | Intuit | 89.90 Bn | 69.25 Bn | 3.44 Bn | 857.00 Mn |
| 8 | Relx | 71.97 Bn | 71.07 Bn | - | - |
| 9 | Thomson Reuters | 48.55 Bn | 45.33 Bn | - | - |
| 10 | Materialise | 478.74 Mn | -138.58 Mn | 46.23 Mn | -14.31 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -14.31 Mn |
| Mar 31, 2026 | -13.92 Mn |
| Dec 31, 2025 | -14.10 Mn |
| Sep 30, 2025 | -13.37 Mn |
| Jun 30, 2025 | -12.59 Mn |
| Mar 31, 2025 | -12.01 Mn |
| Dec 31, 2024 | -12.93 Mn |
| Sep 30, 2024 | -12.06 Mn |
| Jun 30, 2024 | -11.94 Mn |
| Mar 31, 2024 | -11.11 Mn |
| Dec 31, 2023 | -10.88 Mn |
| Sep 30, 2023 | -10.32 Mn |
| Jun 30, 2023 | -10.33 Mn |
| Mar 31, 2023 | -9.68 Mn |
| Dec 31, 2022 | -11.73 Mn |
| Sep 30, 2022 | -9.39 Mn |
| Jun 30, 2022 | -9.56 Mn |
| Mar 31, 2022 | -8.77 Mn |
| Dec 31, 2021 | -7.89 Mn |
| Sep 30, 2021 | -7.79 Mn |
API Access
Materialise Research & Development API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=research-and-development&ticker=MTLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "research-and-development", "ticker": "MTLS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=research-and-development&ticker=MTLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();